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Kollaps/Thunderstorm: Reproducible Evaluation of Distributed Systems: Tutorial Paper

Reproducing experimental results is nowadays seen as one of the greatest impairments for the progress of science in general and distributed systems in particular. This stems from the increasing complexity of the systems under study and the inherent complexity of capturing and controlling all variabl...

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Detalles Bibliográficos
Autor principal: Matos, Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7276261/
http://dx.doi.org/10.1007/978-3-030-50323-9_8
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author Matos, Miguel
author_facet Matos, Miguel
author_sort Matos, Miguel
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description Reproducing experimental results is nowadays seen as one of the greatest impairments for the progress of science in general and distributed systems in particular. This stems from the increasing complexity of the systems under study and the inherent complexity of capturing and controlling all variables that can potentially affect experimental results. We argue that this can only be addressed with a systematic approach to all the stages and aspects of the evaluation process, such as the environment in which the experiment is run, the configuration and software versions used, and the network characteristics among others. In this tutorial paper, we focus on the networking aspect, and discuss our ongoing research efforts and tools to contribute to a more systematic and reproducible evaluation of large scale distributed systems.
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spelling pubmed-72762612020-06-08 Kollaps/Thunderstorm: Reproducible Evaluation of Distributed Systems: Tutorial Paper Matos, Miguel Distributed Applications and Interoperable Systems Article Reproducing experimental results is nowadays seen as one of the greatest impairments for the progress of science in general and distributed systems in particular. This stems from the increasing complexity of the systems under study and the inherent complexity of capturing and controlling all variables that can potentially affect experimental results. We argue that this can only be addressed with a systematic approach to all the stages and aspects of the evaluation process, such as the environment in which the experiment is run, the configuration and software versions used, and the network characteristics among others. In this tutorial paper, we focus on the networking aspect, and discuss our ongoing research efforts and tools to contribute to a more systematic and reproducible evaluation of large scale distributed systems. 2020-05-15 /pmc/articles/PMC7276261/ http://dx.doi.org/10.1007/978-3-030-50323-9_8 Text en © IFIP International Federation for Information Processing 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Matos, Miguel
Kollaps/Thunderstorm: Reproducible Evaluation of Distributed Systems: Tutorial Paper
title Kollaps/Thunderstorm: Reproducible Evaluation of Distributed Systems: Tutorial Paper
title_full Kollaps/Thunderstorm: Reproducible Evaluation of Distributed Systems: Tutorial Paper
title_fullStr Kollaps/Thunderstorm: Reproducible Evaluation of Distributed Systems: Tutorial Paper
title_full_unstemmed Kollaps/Thunderstorm: Reproducible Evaluation of Distributed Systems: Tutorial Paper
title_short Kollaps/Thunderstorm: Reproducible Evaluation of Distributed Systems: Tutorial Paper
title_sort kollaps/thunderstorm: reproducible evaluation of distributed systems: tutorial paper
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7276261/
http://dx.doi.org/10.1007/978-3-030-50323-9_8
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